Over the past few decades, biometric identification and verification using facial features has gained prominence both in traditional video surveillance/access control systems and in hand-held devices for daily use. Most of these approaches work under the implicit assumption that the entire face of a subject can be captured with decent quality. However, there are many real-world scenarios where only a partial face is captured or instances when only the eye region of a face is visible, especially for the cases of uncooperative and non-cooperative subjects. Conventional commercial matchers and law enforcement agencies who rely on such matchers to perform face matching for identification will typically run into problems in the case where only the periocular region is available. This is due to the fact that commercial matching algorithms are developed using the entire human face and typically simply cannot deal with partial faces.